The development of pu software

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Cows and not-knowing

The development of pu-software - blog 2

Pu-software is applied philosophy. Pu is a word from the mirdan philosophy. It means: everything we do not know or understand.

In the new blog series "The development of pu software" I share with you the application of the philosophical word pu in software.

The second blog in the series: "Cows and not-knowing", about the mind of big land mammals, which tends to be hard to predict.

Cows and not-knowing

A youngbulllived in asmall herd inanature reserve on the shores of a lake.

He feltstrong, but was, like anyyoung animal,at the bottom ofthehierarchy.One dayhe challengeda seniorbull, it was amistake, he wasexpelled fromthe herd.

The nature reservewas small, sohe could notreally leave,but returningto the herd was impossible too.He took thegambleandswam into the lake, quite far away there wasa small island.There he wassafe from theherd.

A young studentwas working onan ecologicalcomputer model. Can youpredictvegetationin nature reserves near the watereven ifthe water becomes saltierand will flood the nature area more often?A large amount ofdatawasavailable,of vegetation presentat thousands oflocations, of many years.
A small islandgave a biganomaly.The vegetationwas completelydifferent thanyou might expect.The onebullhadchanged the ecosystem ofthe small islandcompletely.

Is vegetation growth predictable with a computer model?
Roughly speaking it is.
And a vastly improved computer model, would it be able to predict the details of the plants growing in all areas?
Not a chance.To predictthe vegetationof this island, the modelshoud have contained theentireworkings of the psycheofthecalfand that ofall hisherd members.

A computer model does not have a chance, the whole of science does not have it, to make predictions in such a detail.

I finished my job in this research and started the next:
What are we able to predict and what not? Where are the boundaries of what we are able to know?
Where does our reason cease to be useful?

The smallest,first step isto recognizehow muchwe do notknowandtryto map it.
To start with that, we could make the not-knowing visible.
When we get used in doing that, I believe we will see a pattern.
Until finally we can create a map, a mental map with what we know and what we do not know.
And we can make it into a science. Just like the rest of science, we will not get those boundaries absolute, but we will change it, by experience and theory.

It will help us to give us an idea where we can book progress, with science or computers and where it is unlikely.
It will also make it easy for us to visualize in science and computers where knowing ends and not-knowing starts.

In fact, I see itas a task forsoftware developers andscientists, toshow the boundarybetween knowing andnot-knowing in their software or scientific field, so it can not be usedfor taskswherethey areincapable of.

How you could do that, I'll tell you in the following blogs. Subscribe to get them in your mailbox.